Requirements

What are we looking for?

• Bachelor’s degree in computer science, Systems Engineering, or a related field.
  
• At least three (3) years of practical experience in full-stack software development.
  
• Strong experience in API development, database integration, and data engineering.
  
• Proven experience building dashboards and data visualization tools.
  
• Experience working with cloud infrastructure and scalable digital systems.
  
• Knowledge or experience in machine learning and AI engineering is an added advantage.
  
• Strong analytical and problem-solving skills.
  
• Professional proficiency in English (written and oral).
  
• Ability to work independently and collaboratively in multidisciplinary and multicultural environments.
  

• Design and build automated dashboards, interactive maps, and advanced data visualisations for CIP digital platforms, including Varscout and other applications.
  
• Develop APIs, MCP servers, and custom integrations to connect CIP knowledge assets with AI-powered tools such as Digital Green’s Farmer.Chat and other conversational AI assistants.
  
• Lead the end-to-end development of the CIP Clearinghouse platform for organizing, discovering, and sharing research outputs with AI-enabled search and visualisation capabilities.
  
• Design and implement digital, AI-based certification systems (e.g., Potato Zero and Mulching initiatives), including data collection workflows and compliance verification systems.
  
• Develop and manage databases, ensure proper data architecture, and support data integration across platforms.
  
• Collaborate with researchers, project teams, and external partners to translate requirements into scalable technical solutions.
  
• Ensure secure, efficient, and scalable digital infrastructure aligned with CIP’s digital policies and standards.
  
• Contribute to machine learning model development and deployment where applicable.
  
• Provide technical documentation, user guidance, and knowledge transfer to internal teams.
  
• Stay up to date with emerging AI, data engineering, and digital transformation trends relevant to agricultural research.